Processing and analysis of Hi-C data on bacteria

• Verfasst von: Hofmann, Andreas [VerfasserIn]
• Verfasst von: Heermann, Dieter W. [VerfasserIn]
• Titel: Processing and analysis of Hi-C data on bacteria
• Verf.angabe: Andreas Hofmann, Dieter W. Heermann
• E-Jahr: 2018
• Jahr: 15 August 2018
• Umfang: 13 S.
• Fussnoten: Gesehen am 04.12.2020
• Titel Quelle: Enthalten in: Bacterial chromatin
• Ort Quelle: New York, NY : Humana Press, 2018
• Jahr Quelle: 2018
• Band/Heft Quelle: (2018), Seite 19-31
• ISBN Quelle: 978-1-4939-8675-0
• DOI: doi:10.1007/978-1-4939-8675-0_2
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Bacteria
• Sach-SW: Hi-C
• Sach-SW: Hi-C data analysis
• K10plus-PPN: 1585117358

Abstract

The study of three-dimensional genome organization has recently gained much attention in the context of novel techniques for detecting genome-wide contacts using next-generation sequencing. These genome-wide chromosome conformation capture-based methods, such as Hi-C, give a deep topological insight into the architecture of the genome inside the cell. This chapter reviews the steps to process next-generation Hi-C sequencing data to generate a final contact probability map. We describe these steps using publicly available Hi-C datasets of different bacteria. We also present strategies to assess the quality of Hi-C datasets.